0.1 Selecting a few users as examples to show the full time serie

load(file = paste0(IO$output_data,"users.Rdata"), verbose = TRUE)
## Loading objects:
##   users
load(file = paste0(IO$tmp_data, "days_pill_trans.Rdata"), verbose = TRUE)
## Loading objects:
##   days
dim(users)
## [1] 12773    33
dim(days)
## [1] 16651    28
pill_trans_users = users[users$user_id %in% unique(days$user_id),]

for(trans in c("on pill","off pill")){
  cat(trans, "\n")
  for(change in c("increase","decrease")){
    cat("\t",change, "\n")
    if(trans == "on pill"){
      pill_trans_users$n_TB_diff = pill_trans_users$n_TB_diff_on_pill
      pill_trans_users$TB_diff = pill_trans_users$TB_diff_on_pill
    }else{
      pill_trans_users$n_TB_diff = pill_trans_users$n_TB_diff_off_pill
      pill_trans_users$TB_diff = pill_trans_users$TB_diff_off_pill
    }
    
    j = which((pill_trans_users$BC == trans) & (pill_trans_users$TB_diff == change))
    this_cat_users = pill_trans_users[j,]
    o = order(abs(this_cat_users$n_TB_diff), decreasing = TRUE)
    user_ids = this_cat_users$user_id[o][1:10]
    
    for(user in user_ids){
      cat("\t\t",user,"\n")
      this_user_days = days[days$user_id == user,]
      
      g = ggplot_user_history(this_user_days, pill_transition = trans)
      print(g)
    }
  }
}
## on pill 
##   increase 
##       07cbc6b7d1dc8a9132ec1a0f8b6bfbe0eb5fb474

##       3be876597361e2c6a2a80e208bb7174724e0fe0e

##       4cd84c23f3e14f94a25041bb70f79f5fc9ea4b88

##       b6f7f4c53b04a93b69689e0bfc77e57dc8909649

##       1e373dfaa7f3f5ddba01073bccc2c1fd566dfded

##       03f51ae00d7291b8baafad260fdb3f12eecce978

##       1728efb05b33ad2a838eb15b2aa792c177c5da63

##       43fb78ba5cdba7ff4474e1c9c345016d53527d26

##       67e738297709e8e99653f67ea5166c975e128a8a

##       20c370ddc4740dfacae37bbc7d7ea9f17eede3f3

##   decrease 
##       77919960f82f961a738c7829b29047962e02d217

##       d48cab24419c8a9fe03f300c0906745626dc29ed

##       00c3da5f81d0a0447025ed3e3d112c90db5ae72e

##       77ee91ac45472d126f2582b6fc5899768ee501be

##       1b59d2627fb4d9a696764e687ec41651fa801a21

##       4450d649fbfc46dad6ca46c8dc66ddaeb441adfb

##       f42736c6e0d4fb65be59705e79ab1dad5a441075

##       963371392a6c124ad4ab9c355e4888d16fe61fb9

##       887784e04620fbc1b762402a64b2a7f85a362ade

##       d965f006bf7d9eaeffd3847d3f93e55bfe70792a

## off pill 
##   increase 
##       1e54913ee421d364f831da6ace198d2e8deff7d9

##       8a2131f0e8a95890f69c26781f7cea27c5b7e94f

##       6abea6bb974f9cea06f585b328140ba92a2ddeee

##       8c05705ba06a6bc5ac0b93c85eb57dd09651d81a

##       eeacca380b88ed2da73841821b8f5355da9d7843

##       5092e7cd07f623efc8f894cdca158589fe3e95a5

##       83333733e278bda81ea1ccd97ac71db17b982e28

##       beb40f0d558cc33802e446e4e492234d8f5502aa

##       286d460f392a48e20403e42081f69652b52214f4

##       04cb7ae6f0451fdca06c635c1b097f00a2320966

##   decrease 
##       c52ca1555f80cbc5ceb858bd2535a40b45f74ff2

##       502798997effd9d606ba2541f388b0bbc1292c8a

##       2baaf2bdc474ff193909ea56de2437d39b4c599c

##       e18a4c4bb2a1abb9bba633aa607c4a1d0c73f29e

##       3108f197c6f41edce1775ccd822f03a54887935e

##       3ba861ef958e1178a2e11e363e36e51d6fe0d4fc

##       8a03c607cf058ea0a649cd63c2d09d3d2198c7d6

##       199fba436a0ac6d68a47cfa0047fff689b43af62

##       36479790a042475b3aeab1f521f83125e837e58a

##       6ac4046d96541196d86221a3565e602374e263fa

0.1.1 Selected users

user_ids = c("1e373dfaa7f3f5ddba01073bccc2c1fd566dfded", # on-pill increase
             "77ee91ac45472d126f2582b6fc5899768ee501be", # on-pill decrease
             "1e54913ee421d364f831da6ace198d2e8deff7d9", # off-pill increase
             "8a03c607cf058ea0a649cd63c2d09d3d2198c7d6" ) # off-pill decrease



for(user in user_ids){
  cat(user,"\n")
  this_user_days = days[days$user_id == user,]
  j = which(users$user_id == user)
  trans = users$BC[j]
  
  cat(trans,"\n")
  if(length(j)>0){
    if(trans %in% c("on pill","off pill")){
      g = ggplot_user_history(this_user_days, pill_transition = trans)
      print(g)
    }
  }
}
## 1e373dfaa7f3f5ddba01073bccc2c1fd566dfded 
## on-off pill 
## 77ee91ac45472d126f2582b6fc5899768ee501be 
## pill 
## 1e54913ee421d364f831da6ace198d2e8deff7d9 
##  
## 8a03c607cf058ea0a649cd63c2d09d3d2198c7d6 
## 
selected_users_days = days[days$user_id %in% user_ids, ]
selected_users_days$user_id = factor(selected_users_days$user_id, levels = unique(selected_users_days$user_id))
selected_users_days$user_id = paste0("user_", as.numeric(selected_users_days$user_id ))
selected_users_days$user_BC = users$BC[match(selected_users_days$user_id, users$user_id)]

save(selected_users_days, file = paste0(IO$tmp_data,"days_selected_users_for_pill_transition_examples.Rdata"))